To optimally cluster the unknowns using contrastive clustering, we need to have supervision on what an unknown instance is. It is infeasible to manually annotate even a small subset of the potentially infinite set of unknown classes. To counter this, we propose an auto-labelling mechanism based on the Region Proposal Network [1]} to pseudo-label unknown instances, as explained in Sec. REF .
The inherent separation of auto-labelled unknown instances in the latent space helps our energy based classification head to differentiate between the known and unknown instances. As elucidated in Sec. REF , we find that Helmholtz free energy is higher for unknown instances.
